Most common disorders affecting human health are not attributable to simple Mendelian (single-gene) inheritance patterns. Rather, the risk of developing a complex disease is often the result of interactions across genes, whereby one gene modifies the phenotype of another gene. These types of interactions can occur between two or more genes and are referred to as epistasis. There are five major types of epistatic interactions, but in human genetics, additive epistasis is most often discussed and includes both positive and negative subtypes. Detecting epistatic interactions can be quite difficult because seemingly unrelated genes can interact with and influence each other. As a result of this complexity, statistical geneticists are constantly developing new methods to enhance detection, but there are disadvantages to each proposed method. In this article, we explore the concept of epistasis, discuss different types of epistatic interactions, and provide a brief introduction to statistical methods researchers use to uncover sets of epistatic interactions. Then, we consider Alzheimer's disease as an exemplar for a disease with epistatic effects. Finally, we provide helpful resources, where nurses can learn more about epistasis in order to incorporate these methods into their own program of research.
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Tohoku Univ, Grad Sch Med, Tohoku Med Megabank Org, Aoba Ku, Sendai, Miyagi 9808573, JapanTohoku Univ, Grad Sch Med, Tohoku Med Megabank Org, Aoba Ku, Sendai, Miyagi 9808573, Japan
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Seoul Natl Univ, Interdisciplinary Program Bioinformat, Seoul, South KoreaSookmyung Womens Univ, Dept Stat, Seoul, South Korea
Kwon, Min-Seok
Oh, Sohee
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Seoul Natl Univ, Dept Stat, Seoul, South KoreaSookmyung Womens Univ, Dept Stat, Seoul, South Korea
Oh, Sohee
Park, Taesung
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Seoul Natl Univ, Interdisciplinary Program Bioinformat, Seoul, South Korea
Seoul Natl Univ, Dept Stat, Seoul, South KoreaSookmyung Womens Univ, Dept Stat, Seoul, South Korea
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Univ Texas Southwestern Med Ctr Dallas, Quantitat Biomed Res Ctr, Dallas, TX 75390 USAUniv Texas Southwestern Med Ctr Dallas, Quantitat Biomed Res Ctr, Dallas, TX 75390 USA
Lee, Sangin
Pawitan, Yudi
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Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, SwedenUniv Texas Southwestern Med Ctr Dallas, Quantitat Biomed Res Ctr, Dallas, TX 75390 USA
Pawitan, Yudi
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Ingelsson, Erik
Lee, Youngjo
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Seoul Natl Univ, Dept Stat, San56-1 Shin Lim Dong, Seoul 151747, South KoreaUniv Texas Southwestern Med Ctr Dallas, Quantitat Biomed Res Ctr, Dallas, TX 75390 USA